Pre-screened and vetted.
Intern AI/Backend Engineer specializing in LLM agents and cloud microservices
Mid-Level Backend Software Engineer specializing in distributed systems and observability
Junior Full-Stack/Cloud Engineer specializing in AI and data-driven applications
Mid-Level Software Engineer specializing in AI systems and full-stack development
Mid-level Machine Learning Engineer specializing in LLMs, multimodal AI, and backend systems
Senior Technical Support Engineer specializing in cloud and container security
Mid-level QA Engineer specializing in manual and automation testing for web, mobile, and APIs
Mid-level AI/ML Engineer specializing in forecasting, MLOps, and generative AI
Principal Data Scientist specializing in LLMs, RAG, and enterprise AI products
Mid-Level Full-Stack & Cloud Engineer specializing in scalable distributed systems
Mid-level Data Engineer specializing in GCP, Spark, and healthcare analytics
Mid-level Backend/Data Engineer specializing in legal data pipelines and APIs
Senior AI/ML Engineer specializing in LLMs and enterprise conversational AI
Entry-level Software Engineer specializing in systems and healthcare data
Senior Full-Stack Engineer specializing in web, mobile, and product growth
Mid-Level Full-Stack Software Engineer specializing in cloud-native APIs and compliance
“Full-stack/backend engineer with healthcare and enterprise experience: built and secured AWS-hosted services for a clinical EHR product that redacts/transforms hospital patient records for pharma customers (e.g., AstraZeneca, Johnson & Johnson). At Cisco, led an incremental Ruby-to-Python/Django migration for a compliance backend, and has deep multi-tenant security experience using Postgres RLS tied to JWT plus DLQ patterns to harden data pipelines.”
Intern Computer Vision/Perception Engineer specializing in LiDAR and autonomous systems
“Robotics/AV-focused engineer who built an end-to-end gesture controller for a GEM e2 autonomous vehicle using YOLOv8 pose and ROS, including model training, ROS perception nodes, and a safety-oriented state machine (stop override + hold-to-register). Also has internship experience at Intramotev integrating LiDAR object detection via Redis pub/sub and performing sensor-frame calibration (roll/pitch correction using ground-plane normals), plus Dockerized deployments and Gazebo-based testing.”
Intern Full-Stack/ML Engineer specializing in LLM applications and mobile development
“Backend engineer who built a serverless AWS Lambda microservices backend for a parenting assistance mobile app, including a personalized recommendation system optimized to sub-500ms via precomputed scoring and DynamoDB caching. Demonstrates strong production pragmatism: CloudWatch-driven performance tuning (provisioned concurrency), zero-downtime phased schema migrations, and robustness patterns like optimistic locking and request deduplication. Also led a refactor of an LLM RAG pipeline to improve retrieval quality and cut latency from ~5s to ~3s.”
Principal Data Strategy & Data Management Leader specializing in enterprise governance and analytics
“Operator/program leader with experience building operating models and execution cadences for data/analytics and energy data services across Entech, HealthEquity, and RealPage. Has launched an undefined energy data management service into regulated enterprise environments and driven cross-functional alignment via dashboards, SLAs, and OKRs—contributing to enterprise wins and a successful company sale.”
Mid-Level Full-Stack Software Engineer specializing in API-first microservices and cloud platforms
“Backend-focused engineer who built a resume processing and job application platform using Python/MongoDB/Streamlit, including OpenAI-powered skill/keyword extraction and recruiter-facing search/filtering. Has hands-on cloud deployment experience on AWS/Azure and executed an on-prem reservation portal migration to Azure using a phased trial-and-cutover approach; also automated CI/CD with Jenkins and GitHub Actions.”
“LLM/agent workflow engineer with healthcare experience (CVS/CBS Health) who built and deployed a production call-insights platform using Azure OpenAI + LangChain/LangGraph, including sentiment and compliance checks. Demonstrates deep HIPAA/PHI handling (tenant-contained processing, redaction, RBAC/encryption/audit logging) and production rigor (testing, eval sets, validation/retries, autoscaling) to scale to thousands of transcripts.”
“Built and deployed a production Retrieval-Augmented Generation (RAG) platform in a healthcare setting to automate clinical documentation review and summarization, targeting near-real-time, explainable outputs. Emphasizes grounded generation to reduce hallucinations, latency optimizations (chunking/embedding reuse), and PHI-safe workflows with access controls, plus strong orchestration experience using Apache Airflow.”